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At least 307 records · Page 17Linked to original sources

USGS2018

Geochemical characterization and modeling of regional groundwater contributing to the Verde River, Arizona between Mormon Pocket and the USGS Clarkdale gage

We use synoptic surveys of stream discharge, stable isotopes, and dissolved noble gases to identify the source of groundwater discharge to the Verde River in central Arizona. The Verde River more than doubles in discharge in Mormon Pocket over a 1.4 km distance that includes three discrete locations of visible spring input to the river and other diffuse groundwater inputs. A detailed study of the Verde River between Mormon Pocket and the USGS Clarkdale Gage was conducted to better constrain the location of groundwater inputs, the geochemical signature and constrain the source of groundwater input. Discharge, water quality parameters (temperature, pH, specific conductance, and dissolved oxygen), stable isotopes (δ18O and δ2H), noble gases (He, Ne, Ar, Kr and Xe), and radon (222Rn) from river water were collected. Groundwater samples from springs and wells in the area were collected and analyzed for tracers measured in the stream along with some additional analytes (major ions, strontium isotopes (87Sr/86Sr), carbon-14, δ13C, and tritium). Groundwater isotopic signature is consistent with a regional groundwater source. Groundwater springs discharging to the river have a depleted stable isotopic signature indicating recharge source up to 1000 m higher than the discharge location in the Verde River and are significantly fresher than stream water. Spring water has a radiocarbon age of several thousand years and some areas have tritium less than the laboratory reporting level or low concentrations of tritium (1.5 TU). The strontium isotopes indicate groundwater interaction with tertiary volcanic rock and Paleozoic sedimentary rocks. Along the study reach with distance downstream, Verde stream water chemistry shows increased 222Rn, freshening, increased 4He, and isotopic depletion with distance downstream. We estimated total groundwater discharge by inverting a stream transport model against 222Rn and discharge measured in the stream. The salinity, 4He, and stable isotope composition of discharging groundwater was then estimated by fitting modeled values to observed in-stream values. Estimated groundwater inflow to the stream was well within the ranges observed in springs, indicating that the main source of streamflow is deep, regional groundwater. These results show that synoptic surveys of environmental tracers in streams can be used to estimate the isotopic composition and constrain the source of groundwater discharging to streams. Our data provide direct field evidence that deep, regional groundwater discharge can be a significant source of streamflow generation in arid, topographically complex watersheds.

Arizona↗

USGS2022

Stable isotopes provide insight into sources and cycling of N compounds in the Sacramento-San Joaquin Delta, California, USA

River deltas and their diverse array of aquatic environments are increasingly impacted by anthropogenic inputs of nitrogen (N). These inputs can alter the N biogeochemistry of these systems and promote undesirable phenomena including harmful algae blooms and invasive aquatic macrophytes. To examine N sources and biogeochemical processes in the Sacramento-San Joaquin Delta, a river delta located in central California, USA, that is fed primarily by the Sacramento River, we utilized a multi-tracer approach that measured N species concentrations and stable isotope values monthly from April 2011 to November 2012 in samples collected from the channelized mainstem of the Sacramento River, two channelized distributaries of the Sacramento River, and the Cache Slough Complex, a network of Sacramento River tributaries and shallow water wetland habitat. We found that the Sacramento River and its channelized distributaries received N primarily in the form of NH 4 + from treated wastewater effluent and that NH 4 + was lost rapidly while NO 3 − was gained more slowly during subsequent downstream transit, driven by an array of biogeochemical processes whose identities could be constrained via examination of stable isotope values. The Cache Slough Complex, which was characterized by lower net flows and higher water residence times than the Sacramento River and its distributaries, received variable inputs of low conductivity water elevated in NH 4 + from the Sacramento River and higher conductivity water elevated in NO 3 − from landward tributaries. Deviations from expected conservative mixing of these sources were spatially variable but broadly indicative of local inputs of treated wastewater effluent NO 3 − , conversion of Sacramento River NH 4 + to NO 3 − via nitrification, uptake of NH 4 + and NO 3 − by phytoplankton, and remineralization of organic N. These findings highlight both the diversity in N dynamics in anthropogenically impacted river delta environments and the utility of a multi-tracer approach in constraining these processes in such complex systems.

California↗

USGS2023

Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama

Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scales. First, the surface water LSTM model with extensive dynamic (precipitation and other weather variables) and static (basin characteristics) inputs predicted the main characteristics of streamflow for six years at 19 gauged basins in Alabama. The model tended to underestimate extremely high streamflow but adding drainage density as an input feature slightly improved the predictions of extreme events. Second, to predict the groundwater depth evolution, a groundwater LSTM (GW-LSTM) model was proposed and applied using static inputs capturing the aquifers' hydrogeological properties and dynamic inputs of meteorological information. Three precipitation scenarios were also explored to evaluate the groundwater hydrograph evolution in the next two decades. The GW-LSTM model predicted the general trend of daily groundwater depth fluctuations (at 21 wells distributed across Alabama from 1990 to 2021) including most extremely high groundwater levels, and recovered groundwater depth for locations withheld from model training and validation. This study, therefore, extended the application of LSTMs in quantifying the spatiotemporal evolution of surface water and groundwater, two manifestations of a single integrated resource.

Alabama↗

USGS2001

Processes regulating watershed chemical export during snowmelt, fraser experimental forest, Colorado

In the Central Rocky Mountains, snowfall dominates precipitation. Airborne contaminants retained in the snowpack can affect high elevation surface water chemistry during snowmelt. At the Fraser Experimental Forest (FEF), located west of the Continental Divide in Central Colorado, snowmelt dominates the annual hydrograph, and accounts for >95% of annual stream water discharge. During the winters of 1989-1993, we measured precipitation inputs, snowpack water equivalent (SWE) and ion content, and stream water chemistry every 7-10 days along a 3150-3500 m elevation gradient in the subalpine and alpine Lexen Creek watershed. The study objectives were to (1) quantify the distribution of SWE and snowpack chemical content with elevation and aspect, (2) quantify snowmelt rates, temperature of soil, snowpack, and air with elevation and aspect, and (3) use change in upstream-downstream water chemistry during snowmelt to better define alpine and subalpine flowpaths. The SWE increased with elevation (P < 0.001) and was greater on NE aspects (P < 0.05). Subalpine soils were unfrozen. Snowmelt occurred throughout winter at low elevation (3150 m), SE aspect stations. By snowpack peak water equivalent (PWE), the snowpack lost about a third (0.24 m) of its moisture. The subalpine snowpack had warm (> - 3??C) temperatures throughout winter which resulted in significant snowpack ion loss. By snowpack PWE in mid May, the snowpack had lost almost half the cumulative precipitation H+, NH4+, and SO42- inputs and a third of the NO3- input. Windborne soil particulate inputs late in winter increased snowpack base cation content. Variation in subalpine SWE and snowpack ion content with elevation and aspect, and wind redistribution of snowfall in the alpine resulted in large year-to-year differences in the timing and magnitude of SWE, PWE, and snowpack ion content. The alpine stream water ion concentrations changed little during snowmelt indicating meltwater passed quickly through surface porous soils and was well mixed before entering the stream. Conversely, subalpine stream water chemistry was diluted during snowmelt suggesting much melt water moved to the stream as shallow subsurface lateral flow. Published by Elsevier Science B.V.

Journal of Hydrology↗

USGS2002

Spatial and temporal variability of trace element concentrations in an urban subtropical watershed, Honolulu, Hawaii

Trace metal concentrations in soils and in stream and estuarine sediments from a subtropical urban watershed in Hawaii are presented. The results are placed in the context of historical studies of environmental quality (water, soils, and sediment) in Hawaii to elucidate sources of trace elements and the processes responsible for their distribution. This work builds on earlier studies on sediments of Ala Wai Canal of urban Honolulu by examining spatial and temporal variations in the trace elements throughout the watershed. Natural processes and anthropogenic activity in urban Honolulu contribute to spatial and temporal variations of trace element concentrations throughout the watershed. Enrichment of trace elements in watershed soils result, in some cases, from contributions attributed to the weathering of volcanic rocks, as well as to a more variable anthropogenic input that reflects changes in land use in Honolulu. Varying concentrations of As, Cd, Cu, Pb and Zn in sediments reflect about 60 a of anthropogenic activity in Honolulu. Land use has a strong impact on the spatial distribution and abundance of selected trace elements in soils and stream sediments. As noted in continental US settings, the phasing out of Pb-alkyl fuel additives has decreased Pb inputs to recently deposited estuarine sediments. Yet, a substantial historical anthropogenic Pb inventory remains in soils of the watershed and erosion of surface soils continues to contribute to its enrichment in estuarine sediments. Concentrations of other elements (e.g., Cu, Zn, Cd), however, have not decreased with time, suggesting continued active inputs. Concentrations of Ba, Co, Cr, Ni, V and U, although elevated in some cases, typically reflect greater proportions attributed to natural sources rather than anthropogenic input. ?? 2002 Elsevier Science Ltd. All rights reserved.

Applied Geochemistry↗

USGS2010

Nitrate in groundwater of the United States, 1991-2003

An assessment of nitrate concentrations in groundwater in the United States indicates that concentrations are highest in shallow, oxic groundwater beneath areas with high N inputs. During 1991-2003, 5101 wells were sampled in 51 study areas throughout the U.S. as part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) program. The well networks reflect the existing used resource represented by domestic wells in major aquifers (major aquifer studies), and recently recharged groundwater beneath dominant land-surface activities (land-use studies). Nitrate concentrations were highest in shallow groundwater beneath agricultural land use in areas with well-drained soils and oxic geochemical conditions. Nitrate concentrations were lowest in deep groundwater where groundwater is reduced, or where groundwater is older and hence concentrations reflect historically low N application rates. Classification and regression tree analysis was used to identify the relative importance of N inputs, biogeochemical processes, and physical aquifer properties in explaining nitrate concentrations in groundwater. Factors ranked by reduction in sum of squares indicate that dissolved iron concentrations explained most of the variation in groundwater nitrate concentration, followed by manganese, calcium, farm N fertilizer inputs, percent well-drained soils, and dissolved oxygen. Overall, nitrate concentrations in groundwater are most significantly affected by redox conditions, followed by nonpoint-source N inputs. Other water-quality indicators and physical variables had a secondary influence on nitrate concentrations.

Environmental Science & Technology↗

USGS1997

Risk of nitrate in groundwaters of the United States - A national perspective

Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as 'input' factors (population density end the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and 'aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as `input' factors (population density and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and `aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.

Environmental Science & Technology↗

USGS2004

Record of late Pleistocene glaciation and deglaciation in the southern Cascade Range. I. Petrological evidence from lacustrine sediment in Upper Klamath Lake, southern Oregon

Petrological and textural properties of lacustrine sediments from Upper Klamath Lake, Oregon, reflect changing input volumes of glacial flour and thus reveal a detailed glacial history for the southern Cascade Range between about 37 and 15 ka. Magnetic properties vary as a result of mixing different amounts of the highly magnetic, glacially generated detritus with less magnetic, more weathered detritus derived from unglaciated parts of the large catchment. Evidence that the magnetic properties record glacial flour input is based mainly on the strong correlation between bulk sediment particle size and parameters that measure the magnetite content and magnetic mineral freshness. High magnetization corresponds to relatively fine particle size and lower magnetization to coarser particle size. This relation is not found in the Buck Lake core in a nearby, unglaciated catchment. Angular silt-sized volcanic rock fragments containing unaltered magnetite dominate the magnetic fraction in the late Pleistocene sediments but are absent in younger, low magnetization sediments. The finer grained, highly magnetic sediments contain high proportions of planktic diatoms indicative of cold, oligotrophic limnic conditions. Sediment with lower magnetite content contains populations of diatoms indicative of warmer, eutrophic limnic conditions. During the latter part of oxygen isotope stage 3 (about 37-25 ka), the magnetic properties record millennial-scale variations in glacial-flour content. The input of glacial flour was uniformly high during the Last Glacial Maximum, between about 21 and 16 ka. At about 16 ka, magnetite input, both absolute and relative to hematite, decreased abruptly, reflecting a rapid decline in glacially derived detritus. The decrease in magnetite transport into the lake preceded declines in pollen from both grass and sagebrush. A more gradual decrease in heavy mineral content over this interval records sediment starvation with the growth of marshes at the margins of the lake and dilution of detrital material by biogenic silica and other organic matter.

Oregon↗

USGS2001

Evaluation of flash-flood discharge forecasts in complex terrain using precipitation

Operational prediction of flash floods produced by thunderstorm (convective) precipitation in mountainous areas requires accurate estimates or predictions of the precipitation distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds are generally small in size, and small position errors in the forecast or observed placement of the precipitation can distribute the rain over the wrong watershed. In addition to the need for good precipitation estimates and predictions, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the precipitation-rate input data. Different techniques for the estimation and prediction of convective precipitation will be applied to the Buffalo Creek, Colorado flash flood of July 1996, where over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the precipitation was exacerbated by the fact that a significant fraction of the watershed experienced a wildfire approximately two months prior to the rain event. Precipitation estimates from the National Weather Service's operational Weather Surveillance Radar-Doppler 1988 and the National Center for Atmospheric Research S-band, research, dual-polarization radar, colocated to the east of Denver, are compared. In addition, very short range forecasts from a convection-resolving dynamic model, which is initialized variationally using the radar reflectivity and Doppler winds, are compared with forecasts from an automated-algorithmic forecast system that also employs the radar data. The radar estimates of rain rate, and the two forecasting systems that employ the radar data, have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the radar data and forecasts from the dynamic model and the automated algorithm could be operationally useful for input to surface-hydrologic models employed for flood warning. Precipitation data provided by these various techniques at short time scales and at fine spatial resolutions are employed as detailed input to a distributed-parameter hydrologic model for flash-flood prediction and analysis. With the radar-based precipitation estimates employed as input, the simulated flood discharge was similar to that observed. The dynamic-model precipitation forecast showed the most promise in providing a significant discharge-forecast lead time. The algorithmic system's precipitation forecast did not demonstrate as much skill, but the associated discharge forecast would still have been sufficient to have provided an alert of impending flood danger.

Journal of Hydrologic Engineering↗

USGS2014

Spatially robust estimates of biological nitrogen (N) fixation imply substantial human alteration of the tropical N cycle

Biological nitrogen fixation (BNF) is the largest natural source of exogenous nitrogen (N) to unmanaged ecosystems and also the primary baseline against which anthropogenic changes to the N cycle are measured. Rates of BNF in tropical rainforest are thought to be among the highest on Earth, but they are notoriously difficult to quantify and are based on little empirical data. We adapted a sampling strategy from community ecology to generate spatial estimates of symbiotic and free-living BNF in secondary and primary forest sites that span a typical range of tropical forest legume abundance. Although total BNF was higher in secondary than primary forest, overall rates were roughly five times lower than previous estimates for the tropical forest biome. We found strong correlations between symbiotic BNF and legume abundance, but we also show that spatially free-living BNF often exceeds symbiotic inputs. Our results suggest that BNF in tropical forest has been overestimated, and our data are consistent with a recent top-down estimate of global BNF that implied but did not measure low tropical BNF rates. Finally, comparing tropical BNF within the historical area of tropical rainforest with current anthropogenic N inputs indicates that humans have already at least doubled reactive N inputs to the tropical forest biome, a far greater change than previously thought. Because N inputs are increasing faster in the tropics than anywhere on Earth, both the proportion and the effects of human N enrichment are likely to grow in the future.

Proceedings of the National Academy of Sciences of↗

USGS2016

Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model

Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.

Manitoba, Minnesota, Saskatchewan↗

USGS2025

A systematic literature review of forecasting and predictive models of harmful algal blooms in flowing waters

Occurrences of harmful algal blooms (HABs) in rivers challenge the belief that rivers are not susceptible to HABs because of their short residence times and fluctuating hydrology. Here we present a systematic literature review of predictive and forecasting models for HABs in flowing waters, including rivers, flowing in-stream reservoirs (e.g., run-of-river reservoirs and lock-and-dam systems) and tidal or estuarine systems with riverine processes. The review aimed to understand current and historical modeling approaches for predicting and forecasting river HABs, without restricting to specific taxa, such as cyanobacteria, or modeling endpoints. The review included 162 articles published over nearly 50 years, covering more than 80 rivers worldwide. Eutrophic, non-wadable rivers with in-stream obstruction were commonly modeled, though diverse environmental characteristics were reported. Most articles used algal biomass or chlorophyll as modeling endpoints, with a quarter using novel or unique endpoints. Algal toxins motivated model development in 23% of the articles, however just 5% used algal toxins as an endpoint. Only 6% of the articles modeled benthic HABs; the rest focused on pelagic HABs. There was no standard model used for modeling river HABs. Process-based models were more common (59%) than data-driven approaches (37%), with model formulations ranging from simple to complex, which contrasts with a lake-focused literature review of HAB models that found data-driven models were more common. Models in river settings shared similar input variables as those previously identified for lakes, such as water temperature, nutrients, and light availability. However, streamflow and other transport metrics took prominence in river models compared to lake models. Algal cell physiology (such as growth, predation, and motility) was routinely included as input data or as mathematical formulations in process-based models and these processes were frequently identified as an important predictor by the articles’ authors. Conversely, data-driven models rarely included these processes, instead using predictors related to environmental conditions, such as nutrients, water quality, water temperature, and streamflow. These important proxy predictors have apparent success with modeling overall algal biomass (irrespective of taxa) whereas other factors, such as those related to algal physiology and other biological processes, are likely responsible for more subtle shifts in community composition. These differences highlight the influence of data availability, especially for processes that are difficult, time-consuming, or expensive to measure, on model development and model outcomes, raising questions about the selection of modeling inputs and endpoints. Challenges to advancing river HAB modeling include the lack of site-specific model inputs representing key processes (e.g., photosynthetic parameters and predation rates), overlooked riverine environments like the benthos and side/back-channel areas, lack of information on environmental settings, and poorly reported model performance metrics. This review emphasizes opportunities for advancing river HAB modeling by learning from well-honed estuarine models, supporting current forecasting and operationalization efforts, and developing common datasets for river HAB model development and evaluation.

BioRxiv↗

USGS2022

Biogeochemical and ecosystem properties in three adjacent semiarid grasslands are resistant to nitrogen deposition but sensitive to edaphic variability

Drylands have low nitrogen stocks and are predicted to be sensitive to modest increases in reactive nitrogen availability, but direct evidence that atmospheric nitrogen deposition will have sustained effects on dryland ecosystems is sparse and conflicting. We used three long-running in situ nitrogen deposition simulation experiments and a complementary laboratory incubation experiment to address fundamental questions about how nitrogen inputs affect drylands: 1) What are the long- and short-term consequences of nitrogen inputs for biogeochemical and ecosystem properties?; 2) Do these consequences depend on soil moisture availability?; and 3) Does soil texture modify the effects of nitrogen inputs and/or soil moisture availability? In 2011, we established three study sites along a soil texture gradient in Arches National Park with plots receiving 0, 2, 5, or 8 kg N ha -1 annually ( n = 5 per treatment per site). We assessed a suite of biogeochemical metrics over the long- and short-term. To assess longer-term effects, we sampled annually (2013-2019), just prior to spring nitrogen fertilization. To assess short-term effects, we sampled immediately before and after spring nitrogen fertilization in 2013. Additionally, we compared foliar chemistry, soil extracellular enzyme activities, heterotrophic respiration rates, and nitrogen trace gas fluxes at select intervals during the study period (2011-2019). Finally, we conducted a laboratory incubation to measure the individual and interacting effects of soil moisture and nitrogen additions on soil microbial activity. We identified some short-term effects in situ , but no lasting consequences of added nitrogen for any of the metrics measured. In the incubation, soil moisture treatments independently increased heterotrophic respiration rates but did not modify the effects of added nitrogen. In contrast to nitrogen treatments, soil texture was associated with large differences in biogeochemical cycling. Our results oppose the common prediction that coupled dryland biogeochemical cycles are sensitive to nitrogen inputs and suggest that fine scale edaphic heterogeneity is a key driver of dryland ecosystem properties. Synthesis . This study synthesizes a rare, long-term dataset, which provides robust evidence that carbon and nutrient cycling and availability are resistant to realistic levels of atmospheric nitrogen deposition in remote dryland ecosystems.

Utah↗

USGS2015

Reducing fertilizer-nitrogen losses from rowcrop landscapes: Insights and implications from a spatially explicit watershed model

We present conceptual and quantitative models that predict changes in fertilizer-derived nitrogen delivery from rowcrop landscapes caused by agricultural conservation efforts implemented to reduce nutrient inputs and transport and increase nutrient retention in the landscape. To evaluate the relative importance of changes in the sources, transport, and sinks of fertilizer-derived nitrogen across a region, we use the spatially explicit SPAtially Referenced Regression On Watershed attributes watershed model to map the distribution, at the small watershed scale within the Upper Mississippi-Ohio River Basin (UMORB), of: (1) fertilizer inputs; (2) nutrient attenuation during delivery of those inputs to the UMORB outlet; and (3) nitrogen export from the UMORB outlet. Comparing these spatial distributions suggests that the amount of fertilizer input and degree of nutrient attenuation are both important in determining the extent of nitrogen export. From a management perspective, this means that agricultural conservation efforts to reduce nitrogen export would benefit by: (1) expanding their focus to include activities that restore and enhance nutrient processing in these highly altered landscapes; and (2) targeting specific types of best management practices to watersheds where they will be most valuable. Doing so successfully may result in a shift in current approaches to conservation planning, outreach, and funding.

Illinois, Indiana, Iowa, Minnesota, Missouri, Ohio↗

USGS2019

Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models

Eutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km 2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.

Great Lakes↗

USGS2021

Nitrogen and phosphorus sources and delivery from the Mississippi/Atchafalaya River Basin: An update using 2012 SPARROW models

Nitrogen (N) and phosphorus (P) inputs throughout the Mississippi/Atchafalaya River Basin (MARB) have been linked to the Gulf of Mexico hypoxia and water‐quality problems throughout the MARB. To describe N and P loading throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were previously developed based on nutrient inputs and management similar to 1992 and 2002. In this study, refined SPARROW models were developed with higher resolution basin delineation, updated (2012) source inputs, improved calibration (load) targets, and additional statistical techniques than used in the previous SPARROW models. Based on the refined models, consistent with past models, N and P loads/yields were the highest from the central part of the MARB (Corn Belt) and along the Mississippi River. Agricultural activities remained the most important N and P source, but more so for N because its input, which could now be distinguished from atmospheric deposition, could be estimated. Natural loss of P from geologic material throughout the MARB was an important source, contributing about 23% of the total P from the MARB, and resulted in specific areas, such as Kentucky and Tennessee, being larger sources of P than previously estimated. This information can help managers decide where efforts will have the largest effects (highest ranked areas) on reducing nutrient loading to the Gulf hypoxia and what are the most important sources of N and P in these areas.

Mississippi/Atchafalaya River Basin↗

USGS2022

Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration

A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km 2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.

Groundwater↗

USGS2007

Spreadsheet WATERSHED modeling for nonpoint-source pollution management in a Wisconsin basin

Although several sophisticated nonpoint pollution models exist, few are available that are easy to use, cover a variety of conditions, and integrate a wide range of information to allow managers and planners to assess different control strategies. Here, a straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.A straightforward pollutant input accounting approach is presented in the form of an existing model (WATERSHED) that has been adapted to run on modern electronic spreadsheets. As an application, WATERSHED is used to assess options to improve the quality of highly eutrophic Delavan Lake in Wisconsin. WATERSHED is flexible in that several techniques, such as the Universal Soil Loss Equation or unit-area loadings, can be used to estimate nonpoint-source inputs. Once the model parameters are determined (and calibrated, if possible), the spreadsheet features can be used to conduct a sensitivity analysis of management options. In the case of Delavan Lake, it was concluded that, although some nonpoint controls were cost-effective, the overall reduction in phosphorus would be insufficient to measurably improve water quality.

Water Resources Bulletin↗